The {targets} R package offers a superior workflow compared to a script-based approach, addressing several common challenges:
{targets} allows you to define a pipeline of computational steps, specifying the dependencies and relationships between them.{targets}, you only need to update the specific steps affected by a change. It intelligently determines which steps are affected and updates them accordingly, saving time and computational resources.{targets} automatically tracks the relationships between steps and ensures that the results at the end of the pipeline remain valid, even if intermediate steps change.Key advantages of the {targets} workflow over script-based approaches include:
{targets} ensures that changes in one step trigger the re-evaluation of dependent steps, maintaining reproducibility.{targets} selectively executes only the affected steps, optimizing computational efficiency.{targets} provides a clear overview of dependencies, making it easier to manage and scale complex workflows with numerous scripts.{targets} automatically manages input and output files, removing the burden of manually tracking file dependencies and their locations.Open the slides in a new tab here.
_targets.R file.tar_make().tar_target() calls to _targets.R.my-analysis.qmd.tar_outdated().